Title :
Control of sensor information in distributed multisensor systems
Author :
Pao, L.Y. ; Baltz, N.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA
Abstract :
Provides an analysis of error covariance control techniques for allocating sensing resources in distributed, multiprocessor, multisensor systems. We present two algorithms for allocating sensing resources that manage the rates and resolutions at which sensor information from various nodes is processed. An elliptical annulus described by two covariance matrices is used to control the prediction and update covariances in the decentralized Kalman filter. These algorithms allow for nodal autonomy by letting each node control the usage of its own suite of sensors. With a single state filter, these sensor management techniques are shown to result in a discrete periodic Riccati equation
Keywords :
Kalman filters; Riccati equations; covariance matrices; filtering theory; resource allocation; sensor fusion; decentralized Kalman filter; discrete periodic Riccati equation; distributed multisensor systems; elliptical annulus; error covariance control techniques; prediction covariances; sensing resources; sensor information; sensor management techniques; state filter; update covariances; Acoustic sensors; Control systems; Covariance matrix; Multisensor systems; Noise measurement; Resource management; Riccati equations; Sensor phenomena and characterization; Sensor systems; Signal resolution;
Conference_Titel :
American Control Conference, 1999. Proceedings of the 1999
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4990-3
DOI :
10.1109/ACC.1999.786475
